similar to: MATLAB vrs. R

Dear R Users, I've never used R before and my professor has asked us to do some pretty intense programming (or it's intense to me at least). Here is the question: Modify the function myquadrature inside the script so that it returns the quadrature of descrete data using the trapezoidal rule. Modify the call to the function at the bottom of the script so that is uses your modifies

I have found some "issues" (bugs?) with nls confidence intervals ... some with the relatively new "port" algorithm, others more general (but possibly in the "well, don't do that" category). I have corresponded some with Prof. Ripley about them, but I thought I would just report how far I've gotten in case anyone else has thoughts. (I'm finding the code

I have a seasonal time series. I want to calculate the annual mean value of the time series at its peak (say the mean of the three values before the peak, the peak, and the three values after the peak). The peak of the time series might change cycle slightly from year to year. # E.g., nPts <- 254 foo <- sin((2 * pi * 1/24) * 1:nPts) foo <- foo + rnorm(nPts, 0, 0.05) bar <- ts(foo,

PR #7690 points out that if the confidence intervals (+/-1.58 IQR/sqrt(n)) in a boxplot with notch=TRUE are larger than the hinges -- which is most likely to happen for small n and asymmetric distributions -- the resulting plot is ugly, e.g.: set.seed(1001) npts <- 5 X <- rnorm(2*npts,rep(3:4,each=npts),sd=1) f <- factor(rep(1:2,each=npts)) boxplot(X~f) boxplot(X~f,notch=TRUE) I can

[posted to R-devel, no discussion: resubmitting it as a bug, just so it gets logged appropriately] Sorry to report further difficulties with nls and profiling and constraints ... the problem this time (which I didn't check for in my last round of testing) is that the nls profiler doesn't seem to respect constraints that have been set when using the port algorithm. See test code

As of LLVM 3.2, is it possible to use iostream with the MCJIT or interpreter execution engines? I'm getting some errors... Each of these commands correctly prints "hello": echo -e '#include <stdio.h>\nint main(){ printf("hello"); }' | clang -cc1 -emit-llvm-bc -x c++ | lli -use-mcjit echo -e '#include <iostream>\nint main(){ std::cout <<

Hi, I'm trying to develop an histogram method for a class called "FLQuant" which is used by the package FLCore (http://flr-project.org). FLQuant is an extension to "array". There is an as.data.frame method that coerces flquant into a data.frame suitable for lattice plotting. The problem is that when I coerce the object and plot it after it works but if the method is

Hi, I'm trying to develop an histogram method for a class called "FLQuant" which is used by the package FLCore (http://flr-project.org). FLQuant is an extension to "array". There is an as.data.frame method that coerces flquant into a data.frame suitable for lattice plotting. The problem is that when I coerce the object and plot it after it works but if the method is

Dear All - The problem: comment lines in an R function (lines beginning with # ) are *sometimes* removed on leaving the R default editor (same with notepad). I'm working on a Windows machine with R version 2.14.1. An example is below. Couldn't find anything that seemed to relate to this in the Changelog. I don't recall encountering this behavior with previous versions of R. Any

When I try to run the example from Variogram with an lme object, I get an error (although summary works): R : Copyright 2005, The R Foundation for Statistical Computing Version 2.2.1 (2005-12-20 r36812) ISBN 3-900051-07-0 ... > fm1 <- lme(weight ~ Time * Diet, BodyWeight, ~ Time | Rat) Error: couldn't find function "lme" > Variogram(fm1, form = ~ Time | Rat, nint =

(I sent this earlier, but it seems not to have come through, due to problems witkh my system) The following command from appendix A, "a sample session", isnt correct: contour(x, y, fa, nint=15) when used R protests: Warning message: parameter "nint" couldn't be set in high-level plot() function it should probably be nlevels, as used a few lines before. This is

Hi all! I would like to import a matlab or gauss code to R. Could you help me? Bye, Sebasti?n. 2007/6/23, r-help-request en stat.math.ethz.ch <r-help-request en stat.math.ethz.ch>: > Send R-help mailing list submissions to > r-help en stat.math.ethz.ch > > To subscribe or unsubscribe via the World Wide Web, visit >

I have the following code for the minimum and maximum of my prediction interval > y.down=lines(x[x.order], set1.pred[,2][x.order], col=109) > y.up=lines(x[x.order], set1.pred[,3][x.order], col=109) domain=min(x):max(x) polygon(c(domain,rev(domain)),c(y.up,rev(y.down)),col=109) It doesnt seem to shade the right region, it gives me a trapezoid. Any help? Thanks!

been puzzling over this for a day. Summary integer variable to use with histogram, 170,000 rows. Value is day of year. Hist works, lattice histogram with nint does not work (spurious spikes in display), lattice histogram using breaks=c(0:365) works fine. Spike values appear to be sum of two adjacent bins. Want to know if this is a familiar problem, and what the recommended work-around is.

Dear list. I have three histograms and I want to add a vertical abline in a different place in each plot. The next example will plot a vertical line at x=5.5 in the three plots: rnorm(100,5,3) -> A rnorm(100,7,3) -> B rnorm(100,4,1) -> C rep(c("A","B","C"),each=100) -> grp data.frame(G=grp,D=c(A,B,C)) -> data histogram(~ D | G, data=data,

On 10/12/2013 19:47, Jim Grosbach wrote: > > On Dec 10, 2013, at 11:26 AM, Alp Toker <alp at nuanti.com > <mailto:alp at nuanti.com>> wrote: > >> >> On 10/12/2013 18:03, Jim Grosbach wrote: >>>> That causes dissonance between what the compiler sees and what >>>> lit.py sees for no particularly good reason. One of the nice

I have 8 cofactors possibly affecting one and only one variable. I make conditional histograms: <-pdf(file="tst3.pdf",paper="special",width=36,height=36) <-histogram(~Oversized|dat$c1*dat$c2*dat$c5*dat$c6*dat$c7*dat$c8*dat$c9*dat$c10,nint=21,layout=c(32,8),data=dat,type="count") <-dev.off() This works (compliments to R developers!) but it does generate a

Hi, I'm using the R library(car) to draw confidence/prediction ellipses in a scatterplot. >From what i understood the ellipse() function return an ellipse based parameters: shape, center, radius . If i read dataEllipse() function i can see how these parameters are calculated for a confidence ellipse. ibrary(car) a=c(12,12,4,5,63,63,23) b=c(13,15,7,10,73,83,43) v <-

I am trying to test out several mgcv::gam models in a scalar-on-function regression analysis. The following is the 'hierarchy' of models I would like to test: (1) Y_i = a + integral[ X_i(t)*Beta(t) dt ] (2) Y_i = a + integral[ F{X_i(t)}*Beta(t) dt ] (3) Y_i = a + integral[ F{X_i(t),t} dt ] equivalents for discrete data might be: 1) Y_i = a + sum_t[ L_t * X_it * Beta_t ] (2) Y_i

I have fitted a logistic regression model > failed.lr2$call lrm(formula = failed ~ Age + task2 + Age:task2, data = time.long, na.action = na.omit) using the Design package functions and would like to generate a nomogram from this model. the datadist information is generated and stored in > ddist time.long$Age time.long$task2 Low:effect 45